Modeling plants with sensor data

查看全文 作　　者：MA [1]Wei;XIANG [2]Bo;ZHA [1]HongBin;LIU [2]Jia;ZHANG [2]XiaoPeng

机构地区：[1]Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing 100871, China;[2]LIAMA-NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China

出　　处：《Science in China(Series F)》索引2009年第52卷第3期,共12页

基　　金：Supported in part by the National Basic Research Program of China (Grant No. 2004CB318000);the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z301, 2006AA01Z302, 2007AA01Z336);Key Grant Project of Chinese Ministry of Education (Grant No. 103001) 摘　　要：Sensor data, typically images and laser data, are essential to modeling real plants. However, due to the complex geometry of the plants, the measurement data are generally limited, thereby bringing great difficulties in classifying and constructing plant organs, comprising leaves and branches. The paper presents an approach to modeling plants with the sensor data by detecting reliable sharp features, i.e. the leaf apexes of the plants with leaves and the branch tips of the plants without leaves, on volumes recovered from the raw data. The extracted features provide good estimations of correct positions of the organs. Thereafter, the leaves are reconstructed separately by simply fitting and optimizing a generic leaf model. One advantage of the method is that it involves limited manual intervention. For plants without leaves, we develop an efficient strategy for decomposition-based skeletonization by using the tip features to reconstruct the 3D models from noisy laser data. Experiments show that the sharp feature detection algorithm is effective, and the proposed plant modeling approach is competent in constructing realistic models with sensor data. 关键词：检测传感器造型植物三维模型植物建模尖锐特征植物叶片几何形状测量数据

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Modeling plants with sensor data

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